Do Multi‐Model Ensembles Improve Reconstruction Skill in Paleoclimate Data Assimilation?

Parsons, L. A.; Amrhein, Daniel E.; Sanchez, Sara C.; Tardif, Robert; Brennan, M. Kathleen; Hakim, Gregory J.

doi:10.1029/2020ea001467

Cited by 24 publications

(22 citation statements)

References 73 publications

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“…Given the impact of the model prior in reconstructing past ENSO and teleconnections, future work is needed to determine whether the characteristics of past CP and EP El Niño events and their hydroclimate responses reported here are robust to different model priors (L. A. Parsons et al., 2021). Furthermore, additional studies using a prior that incorporates the covariance structure of historical observations (e.g., reanalysis) could potentially reduce uncertainties in data assimilation‐based reconstructions of past climate (Amrhein et al., 2020; Perkins & Hakim, 2020).…”

Section: Discussionmentioning

confidence: 99%

Last Millennium ENSO Diversity and North American Teleconnections: New Insights From Paleoclimate Data Assimilation

Luo

Dee

Stevenson

et al. 2022

Paleoceanog and Paleoclimatol

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El Niño‐Southern Oscillation (ENSO) variability affects year‐to‐year changes in North American hydroclimate. Extra‐tropical teleconnections are not always consistent between El Niño events due to stochastic atmospheric variability and diverse sea surface temperature anomalies, making it difficult to quantify teleconnections using only instrumentally‐based records. Here we use two paleoclimate data assimilation (DA) products spanning the Last Millennium (LM) to compare changes in amplitudes and frequencies of diverse El Niño events during the pre‐industrial period and 20th century, and to assess the stationarity of their North American hydroclimate impacts on multi‐decadal to centennial timescales. Using several definitions for Central Pacific (CP) and Eastern Pacific (EP) El Niño, we find a marked increase in 20th century EP El Niño intensity, but no significant changes in CP or EP El Niño frequencies in response to anthropogenic forcing. The associated hydroclimate anomalies indicate (a) dry conditions across the eastern‐central and northwestern U.S. during CP El Niño and wetter conditions in the same regions during EP El Niño; (b) wet conditions over the southwestern U.S. for both El Niño types. The magnitude of regional hydroclimate teleconnections also shows large natural variability on multi‐decadal to centennial timescales. However, when the entire LM is considered, mean hydroclimate anomalies in North America during CP or EP El Niño are consistent in terms of sign (wet vs. dry). Results are sensitive to proxy data and model priors used in DA products. Inconsistencies between El Niño classification methods underscore the need for improved ENSO diversity classification when assessing precipitation teleconnections.

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Section: Discussionmentioning

confidence: 99%

Last Millennium ENSO Diversity and North American Teleconnections: New Insights From Paleoclimate Data Assimilation

Luo

Dee

Stevenson

et al. 2022

Paleoceanog and Paleoclimatol

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“…We construct the prior using output from climate models with paleoclimate simulations of the last millennium (Supplemental Table 1). We use a multi-model ensemble (MME), which has been found to reduce error relative to single model assimilations [59,96] [96].…”

Section: Priormentioning

confidence: 99%

“…to reduce the effects of covariance bias from any one model [59,96]. We note that we weight each model equally, which effectively treats each model as independent.…”

Section: Caveats and Limitationsmentioning

confidence: 99%

Trends and variability in the Southern Annular Mode over the Common Era

King

Anchukaitis

Allen

et al. 2022

Preprint

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The Southern Annular Mode (SAM) is the leading mode of atmospheric variability in the extratropical Southern Hemisphere and has wide ranging effects on ecosystems and societies. Despite the SAM’s importance, paleoclimate reconstructions disagree on its variability and trends. Here, we use data assimilation to reconstruct the SAM over the last 2000 years using temperature and drought-sensitive climate proxies. Our method does not assume a stationary relationship between proxy records and the SAM over an instrumental calibration period, so our reconstruction is less sensitive to the teleconnection variability that has hindered previous reconstructions. Our approach also allows us to identify critical paleoclimate records and quantify reconstruction uncertainty through time. We find no evidence for a forced response in SAM variability prior to the 20th century. We also find the modern positive trend is outside the range of the prior 2000 years, but only on multidecadal time scales.

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“…Cannon, 2018;Vrac, 2018;Galmarini et al, 2019), but these methods have thus far seen little use in paleoclimate DA contexts. Instead, a more common solution is to assimilate a multi-model ensemble (Parsons et al, 2021;King et al, 2021King et al, , 2022. Users may enact this using a single multi-model prior (e.g.…”

Section: Climate Model Biasesmentioning

confidence: 99%

“…Users may enact this using a single multi-model prior (e.g. Parsons et al, 2021;King et al, 2022), or by performing an ensemble of assimilations using different single-model priors (e.g. King et al, 2021).…”

Section: Climate Model Biasesmentioning

confidence: 99%

DASH: A MATLAB Toolbox for Paleoclimate Data Assimilation

King

Tierney

Osman

et al. 2023

Preprint

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Abstract. Paleoclimate data assimilation (DA) is a novel tool for reconstructing past climates that directly integrates proxy records with climate model output. Despite the potential for DA to expand the scope of quantitative paleoclimatology, these methods remain difficult to implement in practice due to the multi-faceted requirements and data handling necessary for DA reconstructions, the diversity of DA methods, and the need for computationally efficient algorithms. Here, we present DASH, a MATLAB toolbox designed to facilitate paleoclimate DA analyses. DASH provides command line and scripting tools that implement common tasks in DA workflows. The toolbox is highly modular and is not built around any specific analysis, and thus DASH supports paleoclimate DA for a wide variety of time periods, spatial regions, proxy networks, and algorithms. DASH includes tools for integrating and cataloguing data stored in disparate formats, building state vector ensembles, and running proxy (system) forward models. The toolbox also provides optimized algorithms for implementing ensemble Kalman filters, particle filters, and optimal sensor analyses with variable and modular parameters. This paper reviews the key components of the DASH toolbox and presents examples illustrating DASH's use for paleoclimate DA applications.

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Do Multi‐Model Ensembles Improve Reconstruction Skill in Paleoclimate Data Assimilation?

Cited by 24 publications

References 73 publications

Last Millennium ENSO Diversity and North American Teleconnections: New Insights From Paleoclimate Data Assimilation

Last Millennium ENSO Diversity and North American Teleconnections: New Insights From Paleoclimate Data Assimilation

Trends and variability in the Southern Annular Mode over the Common Era

DASH: A MATLAB Toolbox for Paleoclimate Data Assimilation

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